Deep Dive Into Big Data

Shifting Gears To Data Centric Solutions

Who We Are

Love For Data is an emerging predictive analytics company that works with businesses by utilizing publicly available data and incorporating it with organizational data to come up with actionable insights. Our cost effective platform aggregates, organizes and analyzes millions of data points across multiple data sources and provides access to these insights through dashboards, reports, visualization and Application Program Interfaces (APIs). Our clients successfully use our data services to better understand competition, monitor their brand, optimize their processes and personalize their offerings amongst many other benefits.

At LFD , we use data science to bring together intelligent businesses and connected customers to deliver more personalized and relevant customer experience.

After data collection, data is preprocessed for the analysis. This includes data cleaning, normalization, handling missing values etc. Data cleaning involves the removal of unwanted, incomplete or incorrect data from the database.

Feature Engineering involves the use of domain knowledge of data to develop features that enable the working of machine learning algorithms. Therefore, important features for model building are designed, using various variable selection techniques. Statistical concepts are used to identify variables which capture maximum effects.

Model building is the procedure that develops, tests and validates model in terms of best predicting the probability of any outcome. Different machine learning algorithms are tested and their performance evaluated to build tailored algorithms and predictive models for your business.

The last stage is of solution development where variable distribution and correlations among variables is analyzed. The model is then developed using advanced machine learning algorithms with iterations until high accuracies are achieved.